Objectives:

2) Efficiency for triggering prompt muons should be at least as high as in current version

3) Robust against high pile-up

4) Simpler to debug

5) Higher efficiency for long-lived particles

6) Higher efficiency for close muons

7) Use modern CMSSW framework features

Design:

1) Seeding: One inside-out seeding algorithm using

2) Regional (track) reconstruction

3) Matching

4) Final fit and parameter assignment

5) Filter

Aim

This page aims to describe the general code design layout for the new L3 Muon Trigger code. The main concern with the L3 reconstruction is with the high PU runs that will seen post-LS1. There will be a higher tracker hit density and therefore creator number of combinatorics when creating tracks.

Overview

The code is focused around 4 main steps: seeding, trajectory building, matching and fitting to the stand alone muon. The code will focus around two types of seeding: Outside-In (OI) and Inside-out (IO). The aim of the two types of seeding should be to effectively find both prompt and displaced muons, whilst rejecting fake tracks especially at high Pile Up (PU) conditions.

The OI seeding will be state based in order to quickly identify the majority of muon events efficiently. The use of a state based seeding algorithm will be important with the higher track density foreseen, producing a greater number of hit based seeds. However for the muons not correctly identified using the OI-state based seeding, the IO seeding will be based hi. This will be slower than the OI-state based. --> Think about if IOHit was sufficient at finding the displaced tracks: as this type of seeding was more sensitive to the generated distance from the beamspot was usually out.

Tasks/Concepts

The power of using iterative tracking within L3 reconstruction needs to be tested in order to see if it should be incorporated into the design. Even if the actual recipe for using online iterative tracking cannot be used, the general principle of first selecting the 'easy' tracks, and then attempting progressively more difficult tracks should be considered.

A tuneable test metric for each track or collection of tracks should be introduced, which can successfully stop the reconstruction when a suitable tracker track is found. This will be the equivalent of having the filters used in the current design.

One possibility is to have 6 iterations: 3 using OI state based seeding, followed by 3 IO hit based seeding. These 3 iterations for each seeding mechanism will first target high pT prompt muons, then low pT prompt muons and finally displaced muons. With this format of iterations, additional iterations can be included in the future, and iterations deemed to have poor performance can be removed.

The seeding for the IO-hit based algorithm could be based off of the same method as the current online iterative tracking; which takes pixel tracks.

Comments from Current Design

The trajectory seed builder for OIState uses: TSGForRoadSearch: class generates hit-less TrajectorySeed from a given Track (=L2 cand). the original error matrix of the Track is adjusted (configurable). In particular for OIState: TSGForRoadSearch::makeSeeds_3.